Probabilistic analysis of stationary batteries performance to deal with renewable variability

Ivo C. Costa, Mauro A. Da Rosa, Leonel M. Carvalho, Filipe J. Soares, Leonardo Bremermann, Vladimiro Miranda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Stationary batteries are currently seen as an interesting solution to deal with the variability of the renewable energy sources. In the same way as other types of storage, e.g. pumped-hydro units, this new type of storage equipment can improve the use of Renewable Energy Sources (RES). Additionally, the stationary batteries location in the grid is not as physically constrained as other storage systems and can be optimally selected to maximize its overall benefits. This paper proposes a new methodology to represent the unique stochastic behavior of stationary batteries while integrated into an electrical power system. This methodology includes not only the technical restrictions of this type of storage system but also how its operation strategy affects its lifetime. The methodology was tested on a small test system, which is based on the IEEE-RTS 79, using sequential Monte Carlo simulation as its core to accurately reproduce the chronology of events of stationary batteries. The results of the simulation are focused on the potential impacts of these storage devices not only in terms of renewable energy used but also in the adequacy of supply.

Original languageEnglish
Title of host publication2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479935611
DOIs
Publication statusPublished - 17 Nov 2014
Externally publishedYes

Publication series

Name2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • composite system adequacy assessment
  • sequential Monte Carlo simulation
  • stationary batteries
  • wind power

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